In current triaging workflows, especially those in an emergency setting, a patient presents at a first point of care, where an assessment, such as imaging, is performed. The image data is then sent to a standard radiology workflow, which typically involves: images being uploaded to a radiologist's queue, the radiologist reviewing the images at a workstation, the radiologist generating a report, an emergency department doctor reviewing the radiologist's report, the emergency department doctor determining and contact a specialist, and making a decision of how to treat and/or transfer the patient to a 2nd point of care. This workflow is typically very time-consuming, which increases the time it takes to treat and/or transfer a patient to a specialist. In many conditions, especially those involving stroke, time is extremely sensitive, as it is estimated that in the case of stroke, a patient loses about 1.9 million neurons per minute that the stroke is left untreated (Saver et al.). Further, as time passes, the amount and types of treatment options, such as a mechanical thrombectomy, decrease.
Thus, there is a need in the triaging field to create an improved and useful system and method for decreasing the time it takes to determine and initiate treatment for a patient presenting with a critical condition.